If you consider a career in Data Science, a certification might be helpful. In fact, this field is becoming one of the trendiest domains, and companies are ready to recruit specialists who can make sense of their data.
Being certified is an excellent approach to obtain an advantage and build abilities that are hard to come by in your preferred field. Moreover, it is a way to validate your talents, so recruiters know what they’re getting if they employ you.
This article will help you discover the best Data Science Certification that meets your interests.
What is a Data Science Certificate?
A certificate in data science is intended for professionals who want to improve their abilities or construct a more current portfolio. In addition, certifications that target specific skills or platform training are now being provided at the undergraduate or pre-professional level.
Students with a data science certificate will demonstrate fundamental abilities and an awareness of backend technologies. On the other hand, certificate programs are often shorter in duration than standard academic degrees.
Professionals pursue a graduate degree to improve their careers in data science or obtain skills to shift to a new role. The most common reasons professionals select a graduate certificate over a master’s degree are time and financial constraints.
It is important to know that a Data Science Certification does not replace a graduate degree. Moreover, they are not easier than master’s degree courses. In fact, participants are doing the same classes as data science master’s degree students.
Is it possible to obtain a Data Science Certificate online?
Definitely, in this article, you can find a list of top colleges and IT companies that provide online courses and certifications.
For whom are Data Science Certificates intended?
They are dedicated to people with some computer coding experience or work in firms or enterprises that deal with data. For example, certificate students are likely to have a background in computer science, database management, research, statistics, or marketing.
Participants learn the most recent data management technologies and processes or develop the knowledge to improve job potential.
The following are some key data science certificate elements that professionals find appealing:
- Certification programs are more condensed and can be done on a more self-paced basis.
- Data science certificates are less expensive than master’s degrees.
- Data science certificates can be tailored to a certain topic or set of abilities.
Google Certified Data Engineer
Some people may be surprised by the first certification since it focuses on a different subject. However, we believe that data engineering skills and tasks are comparable to those required by a data scientist.
We also believe you would have a competitive edge since you would be skilled in data science and engineering. Therefore, this field will assess the following topics:
Designing data processing systems: including storage technologies, data pipelines, and other tools such as BigQuery, Dataflow, Apache Spark, and Cloud Composer, as well as data warehousing migration.
Creating and deploying data processing systems: technologies such as Cloud Bigtable and Cloud SQL with storage costs and performance, data cleansing, transformation, and combining data sources.
Implement machine learning models: retraining models with AI Platform Prediction, utilizing GPU, distinctions between regression, classification, supervised and unsupervised models, and their related evaluation metrics.
Providing solution quality: ensuring security and compliance with features such as encryption, Data Loss Prevention API, Cloud Monitoring, and application portability.
Google Data Machine Learning Engineer
This is another certification that is not data science itself but rather a field more particular inside data science, namely machine learning.
Many data scientists are comfortable working in a Jupyter Notebook. So, putting the model in production, on a website, or in a mobile app can be scary. Therefore, it is vital to study machine learning procedures to be more well-rounded and efficient.
Here are some of the elements that this certification will evaluate:
Framing ML problems include translating business concerns into ML use cases using tools such as AutoML, determining the problem type, such as classification or clustering, and evaluating important ML success indicators.
Architecting ML applications include scaling ML solutions using Kubeflow, feature engineering, automation, orchestration, and monitoring technologies.
Improving and sustaining ML solutions by recording models, retraining and tweaking model performance, and improving these pipelines for training.
Microsoft Data Scientist Certification
The Azure Data Scientist certification is one of Microsoft’s most popular data science credentials. It is an associate-level certification that falls somewhere in the center of the data science certification tree.
Usually, participants can join without a prior Microsoft certification. However, it is always worth confirming whether this is the case when you opt to get certified.
We recommend getting the “Microsoft Certified Azure Fundamentals” certification rather than the data scientist certification, which is an intermediate level if you are new to this field.
This Domain is designed for data scientists familiar with Python and machine learning frameworks such as Scikit-Learn, PyTorch, and Tensorflow and wants to create and run machine learning solutions on the cloud.
Therefore, students will learn how to:
- Build end-to-end Microsoft Azure systems.
- Manage Azure machine learning resources.
- Execute experiments and train models.
- Deploy and operationalize machine learning solutions.
- Adopt responsible machine learning.
- Use Azure Databricks to explore, prepare, and model data.
- Link Databricks machine learning processes with Azure Machine Learning.
This program includes five courses that will help you prepare for Exam DP-100: Designing and Implementing a Data Science Solution on Azure.
The test allows you to demonstrate your knowledge and skill in utilizing Azure Machine Learning to operate large-scale applications.
Moreover, This specialty teaches you how to use your current Python and machine learning experience on Microsoft Azure to manage data intake and preparation, model training and deployment, and machine learning solution monitoring.
Each course teaches you the topics and abilities that the test assesses.
A Career Booster
With this certificate, you qualify for data scientist positions such as:
- Data scientist
- Data analyst
- Expert-level Microsoft certifications
- Data & applied scientist
- Delivery data scientist
IBM Data Science Professional Certificate
You will sit through an exam in this data science certification and understand the subject before being tested.
IBM Data Science Professional Certificate focuses on data science, which is beneficial to study and test.
Another advantage is that this curriculum is available through IBM’s Coursera, a well-known company.
IBM Certificate offers you courses to learn:
- The basics of Data Science.
- Python for Data Science, AI & Development
- Python Project for Data Science
- Databases and SQL for Data Science with Python
- Data Analysis with Python
- Data Visualization with Python
- Machine Learning with Python
- Applied Data Science Capstone
In conclusion, we believe you would be more than qualified to be a data scientist if you completed all of these classes.
These certifications cover significant platforms, technologies, and the data science process, including business challenges, data analysis, data science modeling, and machine learning operations and deployment.
Of course, if you apply directly to these firms, you will appear to be a better fit. However, keep in mind that many more opportunities are available to you.